Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 214 493 428 994 685 431 134 61 351 986 285 976 181 884 772 999 91 495 893 319
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 134 214 976 772 181 319 986 91 493 428 NA 495 285 351 NA 994 685 NA 61 884 431 893 999
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 5 2 5 1 5 2 4 5 4 2
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "t" "e" "p" "a" "g" "P" "S" "G" "K" "J"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 4 10 12 16
which( manyNumbersWithNA > 900 )
[1] 3 7 16 23
which( is.na( manyNumbersWithNA ) )
[1] 11 15 18
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 994 986 976 999
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 994 986 976 999
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 994 986 976 999
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "P" "S" "G" "K" "J"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "t" "e" "p" "a" "g"
manyNumbers %in% 300:600
[1] FALSE TRUE TRUE FALSE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE TRUE
which( manyNumbers %in% 300:600 )
[1] 2 3 6 9 18 20
sum( manyNumbers %in% 300:600 )
[1] 6
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "small" "small" "large" "large" "small" "small" "large" "small" "small" "small" NA "small" "small" "small" NA
[16] "large" "large" NA "small" "large" "small" "large" "large"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "small" "small" "large" "large" "small" "small" "large" "small" "small" "small" "UNKNOWN" "small"
[13] "small" "small" "UNKNOWN" "large" "large" "UNKNOWN" "small" "large" "small" "large" "large"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 0 0 976 772 0 0 986 0 0 0 NA 0 0 0 NA 994 685 NA 0 884 0 893 999
unique( duplicatedNumbers )
[1] 5 2 1 4
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 5 2 1 4
duplicated( duplicatedNumbers )
[1] FALSE FALSE TRUE FALSE TRUE TRUE FALSE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 23
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 999
which.min( manyNumbersWithNA )
[1] 19
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 61
range( manyNumbersWithNA, na.rm = TRUE )
[1] 61 999
manyNumbersWithNA
[1] 134 214 976 772 181 319 986 91 493 428 NA 495 285 351 NA 994 685 NA 61 884 431 893 999
sort( manyNumbersWithNA )
[1] 61 91 134 181 214 285 319 351 428 431 493 495 685 772 884 893 976 986 994 999
sort( manyNumbersWithNA, na.last = TRUE )
[1] 61 91 134 181 214 285 319 351 428 431 493 495 685 772 884 893 976 986 994 999 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 999 994 986 976 893 884 772 685 495 493 431 428 351 319 285 214 181 134 91 61 NA NA NA
manyNumbersWithNA[1:5]
[1] 134 214 976 772 181
order( manyNumbersWithNA[1:5] )
[1] 1 5 2 4 3
rank( manyNumbersWithNA[1:5] )
[1] 1 3 5 4 2
sort( mixedLetters )
[1] "a" "e" "g" "G" "J" "K" "p" "P" "S" "t"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 9.0 6.5 6.5 4.5 9.0 2.5 9.0 1.0 4.5 2.5
rank( manyDuplicates, ties.method = "min" )
[1] 8 6 6 4 8 2 8 1 4 2
rank( manyDuplicates, ties.method = "random" )
[1] 8 7 6 5 10 3 9 1 4 2
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 -1.43295010 -2.27817614 0.08998173 1.79937099 1.52399766
[11] -0.16566794 0.54867070 -1.15039510 0.52715497 0.94365527
round( v, 0 )
[1] -1 0 0 0 1 -1 -2 0 2 2 0 1 -1 1 1
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 -1.4 -2.3 0.1 1.8 1.5 -0.2 0.5 -1.2 0.5 0.9
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 -1.43 -2.28 0.09 1.80 1.52 -0.17 0.55 -1.15 0.53 0.94
floor( v )
[1] -1 -1 0 0 1 -2 -3 0 1 1 -1 0 -2 0 0
ceiling( v )
[1] -1 0 0 1 1 -1 -2 1 2 2 0 1 -1 1 1
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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